Technology Lead

Infosys Limited

Sydney

On-site

AUD 98,000 - 102,000

Full time

2 days ago
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Benefits offered by this job

Hybrid work arrangements

Job summary

Infosys Limited in Sydney seeks a Technology Lead to drive data engineering initiatives across the data lifecycle, from ingestion to analytics. You will partner with product and IT teams to deliver reliable data solutions and scalable pipelines.

Ideal candidates have 4–5 years in data engineering, strong SQL and Python skills, data profiling expertise, and a passion for solving complex data challenges in a fast-paced environment. Hybrid work arrangements may apply.

Qualifications

  • Bachelor’s, Master’s, or Doctorate degree in Mathematics, Statistics, Computer Science, or Information Management.
  • 4–5 years of experience in Data Engineering and Data Warehousing.
  • Hands-on experience with advanced SQL and Python.
  • Proficient in data profiling.

Responsibilities

  • Enhance, optimize, and maintain data ingestion, transformation, and extraction pipelines.
  • Collaborate with Product Owner and Chapter Lead to understand priorities and gather requirements.
  • Schedule data pipelines using tools like Control M and Airflow with SLA compliance.
  • Document low-level design, mapping, test cases, and release plans.
  • Provide warranty support to Operations post-production release.

Skills

Advanced SQL
Python
Data profiling

Education

Bachelor’s, Master’s, or Doctorate in Mathematics, Statistics, Computer Science, or Information Management

Job description

About Us

Infosys is a global leader in next-generation digital services and consulting. Over 320,000 of our people work to amplify human potential and create the next opportunity for people, businesses and communities. We enable clients in 59 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer clients, as they navigate their digital transformation powered by cloud and AI. We enable them with an AI-first core, empower the business with agile digital at scale and drive continuous improvement with always-on learning through the transfer of digital skills, expertise, and ideas from our innovation ecosystem. We are deeply committed to being a well-governed, environmentally sustainable organization where diverse talent thrives in an inclusive workplace.

Recognized as the #1 Top Employerin Australia for the second year in a row, Infosys offers a workplace where careers grow with purpose. As an AI‑first organization, we empower our people to work on next‑generation technologies, continuously learn, and create impact at scale—supported by a culture rooted in care, inclusion, and excellence.

Role Description

We are looking for a professional who is passionate about technology and problem-solving using technology whether it is a simple issue that enables a user to work faster or a solution that improves efficiency/productivity for a big team, it gives me immense satisfaction. The candidate should be a keen learner and should keep oneself updated with technological improvements and new technologies. The candidate should enjoy finding new innovative methods of doing things and believe that change is the only constant.

If your passion is to build solutions that really make a difference to enterprises, the community and your world, Infosys is the right place for you.

Role: Technology Lead

Location: Sydney

Salary: AUD $ 97,749 - $101,688 Annual Gross

Please Note: - The above salary range is only indicative and maybe subject to suitable enhancements, based on internal company processes

Flexible working arrangements (hybrid, reviewed case-by-case basis).

Roles and Responsibilities
  • Enhance, optimize, and maintain existing data ingestion, transformation, and extraction pipelines and assets built for reporting and analytics on the Unified Data platform.
  • Work with the Product Owner and Chapter Lead to understand quarterly priorities and OKRs, and gather detailed requirements from initiative owners or program sponsors based on planned Epics.
  • Perform data wrangling, profiling, and analysis for new datasets ingested from source systems and those derived from existing datasets using on-premises and cloud-native tools.
  • Coordinate with other teams for planning, design, governance, engineering, and release management to ensure timely and accurate delivery of data and services.
  • Build new data assets and pipelines tailored to downstream requirements using Big Dat or Natural language processing(NLP) (e.g., datasets for Tableau vs. TM1 cubes).
  • Document low-level design, source-to-column mapping, test cases, production release implementation plans, and operational support manuals.
  • Schedule data pipelines using tools like Control M and Airflow, ensuring correct upstream dependencies and SLA compliance.
  • Provide warranty support to Operations post-production release and update documentation accordingly.
  • Collaborate with multiple business and IT teams to deliver the final outcome.
  • Ensuring effective communication and collaboration across multiple stakeholders and business units of Optus.
  • Gaining functional knowledge by reviewing the existing code base to better understand the Optus domain.
  • Adapting to an agile environment with constant change and diverse challenges in a competitive market.
  • Working effectively within tight timeframes.
  • Balancing the needs of multiple stakeholders across various business initiatives and managing competing priorities to ensure timely resolution.
  • The ability to develop sensible alternate solutions, utilising your market knowledge whilst working both quickly and accurately to meet short deadlines and manage competing priorities.
  • Education:
    • Bachelor’s, Master’s, or Doctorate degree in Mathematics, Statistics, Computer Science, or Information Management.
  • Work Experience:
    • 4–5 years of experience in Data Engineering and Data Warehousing.
  • Technical Skills:
    • Hands-on experience with advanced SQL and Python.
    • Proficient in data profiling.
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